Inductive Logic Programming (ILP) induces concepts from a set of negative examples, a set of positive examples, and background knowledge. ILP has been applied on tasks in areas such as natural language processing, finite element mesh design, network mining, robotics, drug discovery, and more. These datasets typically contain both numerical...
Entre más grande sea la base de conocimientos, es más probable que la hipótesis final esté construida con más cláusulas, por lo tanto es más difícil de interpretar. De este inconveniente nace la necesidad de crear nuevas cláusulas que permitan crear hipótesis con menos cláusulas, que además aporten información, que...
The classification of large amounts of data is a challenging task in machine learning, which only some few classifiers can handle. In this paper we propose a Parallel Classifier based on Mixture of Experts (PCME)to handle this challenging task. The PCME is a novel algorithm since it allows us to...